The prevalence of a disease plays an important role in your probability of having it given you test positive.

This is less relevant for testing positive for SARS-CoV-2 **infection** since RT-PCR rarely (if ever) has false positives. However, this may be relevant for antibody tests, which are less precise. Here is a quick explainer for how this works.

The numbers in this explainer are made up. Are some real numbers for the sensitivity and specificity (as it stands today): `r tufte::margin_note("1. https://www.mayoclinicproceedings.org/article/S0025-6196(20)30365-7/fulltext <br> 2. https://www.fda.gov/media/136151/download <br> 3. https://www.centerforhealthsecurity.org/resources/COVID-19/serology/Serology-based-tests-for-COVID-19.html")`

RT-PCR:

`r emo::ji("point_right")`

sensitivity: can be as low as 70%, maybe closer to 90%¹

`r emo::ji("point_right")`

specificity: ~100%²

Antibody test (depends on the test, the one approved in US³):

`r emo::ji("point_right")`

sensitivity: 93.8%

`r emo::ji("point_right")`

specificity: 95.6%